marginal: Estimate Marginal distribution
In vincenzocoia/copsupp: Vine Copulas made easy

Description Usage Arguments Details Value

Estimates the marginal distribution of a univariate sample, either by MLE (if a parametric family is specified) or empirical distribution (edf, with kernel density pdf) otherwise.

marginal(
  x,
  dist.name = NULL,
  ecdf.split = NULL,
  init.val = NULL,
  in.range = NULL,
  soften.cdf = TRUE,
  eqf.type = 1
)

`x`	Vector representing the univariate sample drawn from the distribution to be estimated.
`dist.name`	String; name of the parametric family of distributions, if you don't want the edf. Use R's naming conventions for distributions ahead of the d/p/q/r. For example, the Normal distribution would be `"norm"`.
`ecdf.split`	Numeric; real number for which to fit the specified model for data above such number, and empirical distribution to be fit below.
`init.val`	If a parametric distribution is specified (through `dist.name`), this should be the initial value specification for the parameters. Could be (1) a vector, in which the order provided will correspond to the order given in the R documentation for that distribution, or (2) a list with names being the parameter names, or (3) remain `NULL` in which case default parameter values are used (if there even are defaults).
`in.range`	The same as the argument in `rnlm` – a function that takes the parameter values and returns `TRUE` if that value of the parameter is "proper"; `FALSE` otherwise.
`soften.cdf`	Logical; should the cdf be modified so that it never returns the boundary cases 0 or 1? (uses 0.5/n or 1-0.5/n instead, where n is amount of data)
`eqf.type`	If the empirical quantile function is being estimated, this argument specifies the type of quantile algorithm to use, as in the `type` argument of the `quantile` function. In particular, an integer between 1 and 9.